MB104 Mathematics IV

Faculty of Informatics
Spring 2010
Extent and Intensity
2/2. 4 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
Mgr. Michal Bulant, Ph.D. (lecturer)
RNDr. Jana Komárková (seminar tutor)
Mgr. Jitka Kühnová, Ph.D. (seminar tutor)
Mgr. Lenka Mžourková Macálková (seminar tutor)
Mgr. Petr Pupík (seminar tutor)
Mgr. Veronika Trnková (seminar tutor)
Mgr. Milan Werl, Ph.D. (seminar tutor)
prof. RNDr. Radan Kučera, DSc. (assistant)
Guaranteed by
prof. RNDr. Jan Slovák, DrSc.
Faculty of Informatics
Timetable
Mon 12:00–13:50 D1, Wed 12:00–13:50 D1
  • Timetable of Seminar Groups:
MB104/01: Mon 16:00–17:50 B007, J. Kühnová
MB104/02: Thu 18:00–19:50 B007, P. Pupík
MB104/03: Fri 8:00–9:50 B007, V. Trnková
MB104/04: Fri 10:00–11:50 B007, V. Trnková
MB104/05: Wed 8:00–9:50 B003, M. Werl
MB104/06: Wed 10:00–11:50 B003, M. Werl
MB104/07: Mon 18:00–19:50 B007, J. Kühnová
MB104/08: Tue 12:00–13:50 B003, P. Pupík
MB104/09: Mon 18:00–19:50 B011, L. Mžourková Macálková
MB104/10: Tue 18:00–19:50 B007, L. Mžourková Macálková
MB104/11: Fri 10:00–11:50 B011, J. Komárková
MB104/12: Fri 12:00–13:50 B007, J. Komárková
Prerequisites
Recommended: Calculus and linear algebra.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 16 fields of study the course is directly associated with, display
Course objectives
The last part of the block Mathematics I-IV, for the brief content of the whole block see Mathematics I MB101. The main objectives can be summarized as follows: to understand basic concepts and tools of Algebra; to understand basic concepts and tools of Probability and Statistics.
Syllabus
  • Abstract mathematical structures: groups, algebras, lattices, rings, fields, divisibility, prime numbers decompositions, Euler theorem. Introduction to probability theory and statistics: Probality functins and their properties, conditional probability, Bayes formula, random quantities, mean value, median, quantil, variance, sequences of random quantities, law of large numbers, examples of discrete and continuous distributions, selected applications.
Literature
  • ROSICKÝ, J. Algebra, grupy a okruhy. 3rd ed. Brno: Masarykova univerzita, 2000. 140 pp. ISBN 80-210-2303-1. info
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Popisná statistika. Třetí doplněné vydání. Brno: Masarykova univerzita, 1998. 48 stran. ISBN 8021018313. info
  • BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Teorie pravděpodobnosti a matematická statistika : sbírka příkladů [Budíková, 1996]. 1. vyd. Brno: Masarykova univerzita, 1996. 131 s. ISBN 80-210-1329-X. info
  • ZVÁRA, Karel and Josef ŠTĚPÁN. Pravděpodobnost a matematická statistika. Vyd. 3. Praha: Matfyzpress, 2002. 230 s. ISBN 80-85863-93-6. info
Bookmarks
https://is.muni.cz/ln/tag/FI:MB104!
Teaching methods
There are theoretical lectures, practical demonstration of the computational aspects, and standard tutorial accompanied by homework assessment.
Assessment methods
Two hours of lectures, two hours of presentations of typical problem solutions. Homeworks supported by tutorials. Written test exam.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020.
  • Enrolment Statistics (Spring 2010, recent)
  • Permalink: https://is.muni.cz/course/fi/spring2010/MB104